ABSTRACT
Efficient road infrastructure maintenance is crucial for economic growth and safety but often faces challenges like limited budgets, inefficient resource allocation, and poor scheduling. Traditional approaches relying on fixed schedules or reactive measures leading to premature maintenance. This study investigates the application of Just-In-Time (JIT) principles, a lean construction approach, in road maintenance to optimize resource utilization by aligning interventions with predictive International Roughness Index (IRI) data. Using data from the Addis Ababa City Roads Authority (AACRA), this research identifies road roughness patterns and develops Weibull predictive models to forecast future conditions. These models assist in determining the optimal timing for maintenance interventions based on JIT principles. The study integrates data processing, trend analysis, and forecasting to trigger maintenance before roads reach unacceptable roughness levels, minimizing resource wastage and maximizing cost-effectiveness. Consequently, it can improve road quality and contribute to sustainable urban infrastructure in Addis Ababa, Ethiopia.
